Abstract:
A computing system performs balanced power management based on requirements of graphics scenes in a video game. Based on the requirements of the graphics scenes, the system selects one or more performance metrics to reduce in real-time, where the performance metrics are indicators of video game quality. The system compares estimated power consumption with a power budget after reducing the one or more performance metrics. Based on the requirements of the graphics scenes, the system further selects one or more quality enhancers to activate in real-time while keeping the estimated power consumption within the power budget. Each quality enhancer enhances the video game with respect to a performance metric. The system then displays the video game enhanced by the one or more quality enhancers.
Abstract:
An accelerator for neural network computing includes hardware engines and a buffer memory. The hardware engines include a convolution engine and at least a second engine. Each hardware engine includes circuitry to perform neural network operations. The buffer memory stores a first input tile and a second input tile of an input feature map. The second input tile overlaps with the first input tile in the buffer memory. The convolution engine is operative to retrieve the first input tile from the buffer memory, perform convolution operations on the first input tile to generate an intermediate tile of an intermediate feature map, and pass the intermediate tile to the second engine via the buffer memory.
Abstract:
A method for performing graphics processing of a graphics system in an electronic device and an associated apparatus are provided, where the method includes the steps of: configuring a configurable hardware of the graphics system to be a vertex processing (VP) path in a specific processing phase; utilizing the VP path to perform VP-related tile-based rendering (TBR) operations; configuring the configurable hardware of the graphics system to be a pixel processing (PP) path in another processing phase; and utilizing the PP path to perform PP-related TBR operations. For example, after performing VP-related TBR operations of a specific frame of a plurality of frames is completed, PP-related TBR operations of the specific frame are performed, where after performing the PP-related TBR operations of the specific frame is completed, VP-related TBR operations of another frame of the plurality of frames are performed.
Abstract:
An accelerator for neural network computing includes hardware engines and a buffer memory. The hardware engines include a convolution engine and at least a second engine. Each hardware engine includes circuitry to perform neural network operations. The buffer memory stores a first input tile and a second input tile of an input feature map. The second input tile overlaps with the first input tile in the buffer memory. The convolution engine is operative to retrieve the first input tile from the buffer memory, perform convolution operations on the first input tile to generate an intermediate tile of an intermediate feature map, and pass the intermediate tile to the second engine via the buffer memory.
Abstract:
A method for performing graphics processing of a graphics system in an electronic device and an associated apparatus are provided, where the method includes the steps of: configuring a configurable hardware of the graphics system to be a vertex processing (VP) path in a specific processing phase; utilizing the VP path to perform VP-related tile-based rendering (TBR) operations; configuring the configurable hardware of the graphics system to be a pixel processing (PP) path in another processing phase; and utilizing the PP path to perform PP-related TBR operations. For example, after performing VP-related TBR operations of a specific frame of a plurality of frames is completed, PP-related TBR operations of the specific frame are performed, where after performing the PP-related TBR operations of the specific frame is completed, VP-related TBR operations of another frame of the plurality of frames are performed.